Open menelausyjl opened 1 year ago
In the changelist of the original authors' website, they stated that there was a bug in sample contribution scaling, but it is still kept in PCL.
The fixed version(v7.0):
template< class Real > int Octree< Real >::UpdateWeightContribution( std::vector< Real >& kernelDensityWeights , TreeOctNode* node , const Point3D<Real>& position , typename TreeOctNode::NeighborKey3& neighborKey , Real weight ) { typename TreeOctNode::Neighbors3& neighbors = neighborKey.setNeighbors( node ); if( (int)kernelDensityWeights.size()<TreeNodeData::NodeCount ) kernelDensityWeights.resize( TreeNodeData::NodeCount , 0 ); double x , dxdy , dx[DIMENSION][3] , width; Point3D< Real > center; Real w; node->centerAndWidth( center , w ); width = w; for( int i=0 ; i<DIMENSION ; i++ ) { x = ( center[i] - position[i] - width ) / width; dx[i][0] = 1.125 + 1.500*x + 0.500*x*x; dx[i][1] = -0.25 - 2.*x - x*x; dx[i][2] = 1. - dx[i][1] - dx[i][0]; } // Suppose that the samples are uniformly placed along the middle of the three slices. // Then splatting the points we get coefficients: // 0.125 / 0.75 / 0.125 across the three slices. // Sampling at the center slice we get: // 0.125^2 + 0.75^2 + 0.125^2 = 19/32 const double SAMPLE_SCALE = 1. / ( 0.125 * 0.125 + 0.75 * 0.75 + 0.125 * 0.125 ); weight *= (Real)SAMPLE_SCALE; for( int i=0 ; i<3 ; i++ ) for( int j=0 ; j<3 ; j++ ) { dxdy = dx[0][i] * dx[1][j] * weight; TreeOctNode** _neighbors = neighbors.neighbors[i][j]; for( int k=0 ; k<3 ; k++ ) if( _neighbors[k] ) kernelDensityWeights[ _neighbors[k]->nodeData.nodeIndex ] += Real( dxdy * dx[2][k] ); } return 0; }
The PCL version:
template<int Degree> int Octree<Degree>::NonLinearUpdateWeightContribution( TreeOctNode* node , const Point3D<Real>& position , Real weight ) { TreeOctNode::Neighbors3& neighbors = neighborKey.setNeighbors( node ); double x,dxdy,dx[DIMENSION][3]; double width; Point3D<Real> center; Real w; node->centerAndWidth( center , w ); width=w; const double SAMPLE_SCALE = 1. / ( 0.125 * 0.125 + 0.75 * 0.75 + 0.125 * 0.125 ); for( int i=0 ; i<DIMENSION ; i++ ) { x = ( center[i] - position[i] - width ) / width; dx[i][0] = 1.125 + 1.500*x + 0.500*x*x; x = ( center[i] - position[i] ) / width; dx[i][1] = 0.750 - x*x; dx[i][2] = 1. - dx[i][1] - dx[i][0]; // Note that we are splatting along a co-dimension one manifold, so uniform point samples // do not generate a unit sample weight. dx[i][0] *= SAMPLE_SCALE; } for( int i=0 ; i<3 ; i++ ) for( int j=0 ; j<3 ; j++ ) { dxdy = dx[0][i] * dx[1][j] * weight; for( int k=0 ; k<3 ; k++ ) if( neighbors.neighbors[i][j][k] ) neighbors.neighbors[i][j][k]->nodeData.centerWeightContribution += Real( dxdy * dx[2][k] ); } return 0; }
Hi, yes the Poisson code that PCL uses is quite outdated, but unfortunately nobody found time to update it yet
In the changelist of the original authors' website, they stated that there was a bug in sample contribution scaling, but it is still kept in PCL.
The fixed version(v7.0):
The PCL version: